The application of Artificial Intelligence (AI) algorithms to financial risk management has fundamentally transformed the nature of risk and the tools being used to control and manage it. This paper examines how AI is deployed to manage market risk, including volatility forecasting, portfolio optimisation, stress testing, and sentiment analysis. While many of these models are well-accepted across the industry and underpin many front-office and risk-management processes, they are often limited in dynamic market environments where traditional linearity doesn’t exist and real-time data is king. AI has brought advanced tools that can be applied to large and complex data sets, and that adapt quickly as market conditions change. Reinforcement learning algorithms are now deployed to optimise portfolio weights dynamically. Natural-language processing is also used to augment sentiment analysis, which can be leveraged to assess potential risk. Other forms of AI can be deployed to address challenges that come with more advanced AI models. Explainable AI models provide the opportunity to produce financial outcomes that are more transparent and less opaque while also helping to validate regulatory compliance. Analyzing the applications of AI case studies sheds light on why financial professionals must continue to embrace AI tools, many of which are designed to help them manage risk in an increasingly volatile market environment.

The "live streaming+short video" sales model, with its intuitive, interactive, and convenient characteristics, has had a profound impact on the shopping mode of sportswear. This article aims to analyze the impact of the "live streaming+short video" sales model on the purchasing behavior of sportswear, reveal the relationship and path between various influencing factors, and provide theoretical basis and practical guidance for sportswear brands to formulate more effective marketing strategies. Firstly, based on theoretical analysis, a relationship model was constructed between social influence, product information transparency, anchor credibility, promotional strategy influence, perceived trust, and purchasing behavior; Subsequently, a structural equation model was constructed based on questionnaire survey data to test the theoretical model. The empirical results show that social influence, product information transparency, anchor credibility, and promotional strategies can significantly and positively affect consumer purchasing behavior; Perceived trust plays a mediating role between the aforementioned factors and purchasing behavior. Based on empirical results, it is recommended that sportswear companies use social media for knowledge output to enhance their brand's social influence; Develop various product information disclosure plans to enhance product information transparency; Strengthen the selection of talents within the industry and cultivate professional and trustworthy anchors.

With the deepening of globalization, more and more enterprises are looking towards the international market in search of broader development space. However, international operations not only bring unprecedented opportunities but also accompany various risks. This article delves into the risks enterprises may encounter in international operations, including market, political, economic, exchange rate, legal, and cultural risks, and systematically analyzes the causes, manifestations, and impacts of these risks. Through specific case analyses, this article proposes a series of practical risk management and prevention strategies aimed at helping enterprises build a more robust international operation defense line, ensuring their steady progress in the complex and volatile international market.

In the realm of globalization, green trade barriers have emerged as significant obstacles to the international export of Wuyi mountain rock tea from China. The progressively rigorous green trade barriers enacted by various nations, alongside challenges such as pesticide residues detected in Chinese Wuyi rock tea, have contributed to a notable increase in Wu yi mountain rock tea’s production expenses, thereby undermining its competitiveness in the global marketplace. This study employs a SWOT analysis framework to thoroughly assess the positioning of Wuyi tea exports, with the objective of formulating strategies to navigate green trade barriers and bolster global competitiveness. To accomplish this, the paper will initially address the current developmental status of Wuyi rock tea, followed by an examination of the eco-trade barriers instituted by key importing nations. Furthermore, through the calculation of competitive trade indices, it will investigate the waning competitiveness of Wuyi mountain rock tea as a result of these barriers. Lastly, potential solutions for overcoming the eco-trade challenges will be proposed by using the SWOT analysis methodology. As a result, the paper will offer innovative perspectives for the export advancement of Wuyi mountain rock tea.

This paper explores the study of management research on online recruitment companies, especially to provide a deeper understanding of the management practices of SEEK, Australia’s largest online recruitment company, through a case analysis focusing on challenges related to corporate governance, cost of capital, and company structure. With the development of the internet and information technology, online recruitment platforms offer efficient and convenient hiring methods for businesses and job seekers, but they also bring unique management challenges. By analysing SEEK’s corporate governance structure, including its board composition and compensation policies, this study reveals key issues online recruitment companies face in governance and capital management. Furthermore, the paper examines SEEK’s capital structure and its impact on its operations and growth. Through this case sing of the complexities of managing online recruitment platforms. It highlights both the opportunities created by technological advancements and the governance and financial challenges they face.

In the current economic environment, Chinese consumers tend to pursue products with higher cost-effectiveness, and the phenomenon of consumption downgrading is significant. This article focuses on the development strategy of MUJI in the Chinese market, aiming to explore the competitive advantages and disadvantages of MUJI in the context of consumer downgrading, and propose corresponding development strategies. The study adopted the SWOT analysis method and focused on the operational data and relevant literature of MUJI in the Chinese market. By analyzing its strengths, weaknesses, opportunities, and threats, the study aims to gain a deeper understanding of MUJI's current development status and challenges in the Chinese market. The research data mainly comes from MUJI's financial reports, data from the National Bureau of Statistics, and relevant market research reports, aiming to provide targeted development recommendations for MUJI to adapt to the changes and challenges in the Chinese market. This study found that MUJI should focus on localized design and production, actively engage in digital transformation, strengthen brand value, and increase experiential retail to adapt to the trend of consumer downgrading, in order to achieve sustainable development in the Chinese market.

This paper explores the socioeconomic impact of Nigeria’s high fertility rate and its influence on the country’s economic development. With a fertility rate of 5.14 children per woman in 2022, far exceeding the global average, Nigeria faces significant demographic challenges. The analysis focuses on three critical data points: fertility rate, female tertiary education rate, and female labor force participation rate. The findings highlight how cultural factors, educational attainment, and labor market participation contribute to sustained high fertility rates, particularly in rural areas. Additionally, the paper examines how these factors exacerbate gender inequality and limit economic opportunities for women, thereby hindering Nigeria's overall economic progress. Policy recommendations include promoting female education and workforce participation to help manage population growth and stimulate economic development.

To build a low-carbon and harmonious society that supports sustainable development, China has set forth the significant strategic goal of achieving carbon peaking by 2030 and carbon neutrality by 2060, commonly referred to as the “dual carbon” target. The key to achieving this target lies in scientifically and accurately predicting the timeline for carbon peaking, followed by developing effective carbon reduction paths. Using Jiangsu Province as an example, this study utilizes energy and economic data from 2010 to 2020 and introduces a penalized Lasso-Kaya model to forecast carbon emissions. The applicability of deep learning models, such as LSTM, in carbon peak prediction is also validated. Based on this, three levels of carbon reduction targets were established: baseline, steady progress, and ambitious. Through parameter simulation, the study derives an optimal carbon reduction path for Jiangsu Province through 2060. Consequently, this paper proposes a quantitative assurance mechanism for carbon reduction that maximizes economic growth, providing a valuable reference for future policy intervention.

This paper takes BYD as an example to analyze its financial indicators and conduct a comprehensive DuPont analysis for the period from 2019 to 2023. The analysis reveals that the company achieved significant financial growth during this period. Both operating revenue and net profit showed an upward trend, with particularly strong growth momentum in 2022 and 2023, as net profit increased substantially. The gross profit margin and net profit margin also improved, indicating enhanced operational efficiency and effective cost control. At the same time, BYD's continuous increase in R&D investment has driven technological innovation and product upgrades. The total assets have continued to grow, reflecting the company's business expansion and strengthened capabilities. The cash flow position remains healthy, with net operating cash flow steadily increasing, providing stable financial support for the company. However, BYD faces challenges such as intensified market competition and fluctuations in raw material prices, which necessitate ongoing optimization of business strategies and operational models to maintain its leading position and competitiveness. Overall, BYD has performed outstandingly in the new energy vehicle sector, with promising prospects for future development.

In April 2024, 18 A-share listed companies such as Zhuochuang Zixun, Hengxin Dongfang and Hangtian Hongtu took the lead in setting an example, and first included data assets in the report of the first quarter of 2024. In the era of big data, data assets, as the "new favorite" of enterprises, have a deep influence on improving enterprise competitiveness, guiding enterprise decision-making, and optimizing enterprise operation. At the same time, whether they are included in the table will also affect investors decision-making, and bring impact and volatility to the stock market. This paper adopts the event research method, taking the above 18 trial enterprises as an example, aiming to study the short-term market effect of the data assets in the table. In this paper, it is found that the return rate of enterprises brought by the data assets into the table is not significant, or even decreased. At present, the right confirmation and cost management of data assets need to be further improved.